• Drive real operational impact by delivering models that improve performance, cost, and decision-making at scale
• Full time, permanent opportunity based at our Jetstar Headquarters
• Access to a range of employee benefits, including our staff travel program
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At Jetstar, we’re transforming airline operations through optimisation and decision science — and this role sits at the centre of it

We’re looking for a Manager, Operational Research to lead the development of advanced decision-support models that power smarter, faster, and more consistent operational decision-making across our Jetstar Operations Control Centre (JOCC).

This is a unique opportunity to establish Operational Research (OR) as a core discipline at Jetstar, building a long-term, compounding analytical capability that transforms how we solve complex operational problems.

Working within Operations Delivery, you’ll stay close to real-world challenges while partnering closely with our Technology, Data & Analytics teams to bring sophisticated models into production and daily use.

In this role, you will:

• Lead the design and evolution of optimisation, simulation and predictive models (e.g. tail assignment, recovery, delay prediction).
• Own the end-to-end model lifecycle, from problem framing through to deployment including defining system architecture, building validation and testing frameworks, and establishing logging and monitoring for production models.
• Build a connected suite of models where outputs inform downstream decisions, progressing toward a network digital twin.
• Ensure models are robust, auditable and trusted through strong validation, documentation, and performance frameworks.
• Drive adoption by embedding model outputs into JOCC workflows and decision-making processes.
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You’ll bring:

• Proven experience building and deploying decision-support models (optimisation, simulation, predictive) in production environments.
• Hands-on experience with mathematical optimisation solvers (e.g. Gurobi, CPLEX) including formulating MIP, LP, or CP models from scratch — not just configuring off-the-shelf tools.
• Strong Python engineering skills including model productionisation, API design, and deployment infrastructure (e.g. Docker, containerised workers, REST APIs).
• Strong software engineering capability within OR — comfortable owning the full stack from model logic through to deployed systems (not solely BI, analytics, or consulting)
• Ability to translate complex operational problems into scalable model solutions and manage the full lifecycle.
• Experience working with cloud data platforms (e.g. Snowflake or similar).
• Demonstrated people leadership through developing and leading technical talent.
• Strong stakeholder engagement skills, with the ability to translate technical outputs into clear business insights.
• This is a rare role that combines technical depth with leadership — you'll need to be as comfortable in a codebase as you are in a boardroom.
• This is a deeply hands-on technical leadership role — you will be expected to write, own, and evolve model code in production, not manage vendors or oversee work produced by others.